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Transfer and zero-shot learning for weed species detection with small datasets and unseen classes
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Actually Sparse Variational Gaussian Processes
In this work, we propose a new class of inter-domain variational Gaussian process, constructed by projecting onto a set of compactly …
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Optimal Transport for Offline Imitation Learning
With the advent of large datasets, offline reinforcement learning is a promising framework for learning good decision-making policies …
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Short-term Prediction and Filtering of Solar Power Using State-Space Gaussian Processes
Short-term forecasting of solar photovoltaic energy (PV) production is important for powerplant management. Ideally these forecasts are …
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One-Shot Transfer of Affordance Regions? AffCorrs!
In this work, we tackle one-shot visual search of object parts. Given a single reference image of an object with annotated affordance …
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One-Shot Transfer of Affordance Regions? AffCorrs!
Bayesian Optimization based Nonlinear Adaptive PID Design for Robust Control of the Joints at Mobile Manipulators
In this paper, we propose to use a Nonlinear Adaptive PID controller to regulate the joint variables of a mobile manipulator. Motion of …
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Comparing the carbon costs and benefits of low-resource solar nowcasting
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Parallel MCMC Without Embarrassing Failures
Embarrassingly parallel Markov Chain Monte Carlo (MCMC) exploits distributed computing to scale Bayesian inference to large datasets by …
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Watch Less and Uncover More: Could Navigation Tools Help Users Search and Explore Videos?
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Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels
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Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels